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Bringing analytic rigor to agentic AI for science: The Brain Researcher platform for neuroimaging data analysis
The paper introduces Brain Researcher, a platform that aims to improve the accuracy and reliability of AI agents in scientific analyses, particularly in neuroimaging research. It enhances the selection of analysis…
Beyond Top-K: Replacing Black-Box Retrieval with Interpretable Agentic Operations
A research paper proposes a new method for document search called Reliable Embedding-free Agentic Document-search (READ), which is designed to overcome limitations in current methods for long documents, particularly…
The Effect of Perceived Race and Gender on Police Language Use: Experimental Evidence from VR Simulations
Researchers studied how police officers speak to virtual characters depicted as Black adult males in VR simulations. The study found that most officers speak less deferentially to Black male characters, except for…
SciFigQual-Bench: A Benchmark for Scientific Figure Quality Assessment with Full-Manuscript Context
Researchers propose SciFigQual-Bench, a benchmark for evaluating the quality of scientific figures in computer science papers across five dimensions. The dataset includes over 6,000 images from top conferences between…
Agent-Guided Relational Concept Discovery: Toward Interpretable Surgical Margin Assessment
Researchers propose a new framework called Agent-Guided Concept Discovery for improving deep learning models used in surgical margin assessment. The model learns meaningful concepts directly from data without requiring…
From Static Bibliometrics to Dynamic Knowledge Graphs: An LLM-Powered Framework for Modernizing Science, Technology, and Innovation (STI) Analytics
The paper proposes a new framework that combines traditional bibliometric indicators, dynamic knowledge graphs, and large language models to modernize science, technology, and innovation (STI) analytics. The goal is to…
Non--negative matrix factorization using the extit{R} package extsf{nnmf}
This research presents a new R package for Non-negative Matrix Factorization (NMF) and compares it with two other widely used NMF packages in R. The comparison is based on real-world data instead of simulated datasets…
teLLMe Why (Ain't Nothing but a Jam): Exploratory Causal Analysis of Urban Driving Data
Researchers have developed teLLMe, a system that helps traffic agencies analyze large volumes of video-derived data for studying safety and congestion by answering causal questions about urban driving, such as 'How…
Early Adoption of Agentic Coding Tools by GitHub Projects
This research investigates the adoption and management of agentic coding tools in software development on GitHub. The study analyzes 25,264 agentic pull requests from 2,361 popular repositories to understand (1) how…
Using AI-based Learning Assistants in Higher Education: A Large-Scale Descriptive Analysis
The text describes a study that analyzed the use of an AI-based learning assistant (Syntea) among 77,543 students in distance education, looking at usage patterns across various demographic and structural factors. The…
Exploring the Semantic Gap in Agentic Data Systems: A Formative Study of Operationalization Failures in Analytical Workflows
A study identifies common failures in generating and executing analytical workflows using large language models across finance, human resources, and public safety domains. The authors found five recurring classes of…
TraceLab: Characterizing Coding Agent Workloads for LLM Serving
Researchers collect and release a dataset of approximately 4,300 coding-agent sessions from their own use of Claude Code and Codex. The data shows that coding-agent workloads feature long autonomous loops, long…
AI Healthcare Chatbots as Information Infrastructure: A Large-Scale Study of User-Reported Breakdowns
A study analyzing over 15,000 user reviews of AI healthcare chatbot apps found recurring issues with access barriers, service unreliability, user experience, interaction quality, billing, and customer support. Privacy…
Grading the Grader: Lessons from Evaluating an Agentic Data Analysis System
Researchers evaluated a multi-agent data analysis system called LAMBDA on numerical QRData tasks, using a three-layer human-AI grading cascade to assess its output. They found that both automated graders achieved high…
RetiSEM: Generalising Causal Models for Fragmented Biomedical Data
A new method called RetiSEM is proposed to learn causal models from fragmented biomedical data, where clinical, molecular, and imaging variables are often incomplete or not jointly observed. The method organizes…
AI-driven Optimisation of Quality of Recovery (QoR) in Remote Patient Monitoring
Researchers developed QoR-compact, a shorter version of the Quality of Recovery (QoR) survey, to be used for daily remote patient monitoring. The new version consists of five questions and was found to predict…
An AI research agent drafts these notes from public papers and posts, and each one keeps its source link. Only the folders I choose to publish leave my Obsidian vault.
